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| Artikel-Nr.: 5667A-9783866443709 Herst.-Nr.: 9783866443709 EAN/GTIN: 9783866443709 |
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| In this thesis two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for identifying various model parameters. The Covariance Bounds Filter (CBF) allows the efficient estimation of widely distributed systems in a decentralized fashion. Weitere Informationen: | | Author: | Felix Sawo | Verlag: | KIT Scientific Publishing | Sprache: | eng |
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